Hongwen Dong
- Industrial and Manufacturing Engineering top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Civil and Structural Engineering top 5%
- Mechanical Engineering top 10%
- Computational Mechanics top 5%
- Co-authors
- Yunhui YanKechen SongYu HeJing XuQinggang MengYanyan WangDefu ZhangJie Liu
- Topics
- Infrastructure Maintenance and Monitoring (6 papers)Advanced Image Fusion Techniques (4 papers)Industrial Vision Systems and Defect Detection (4 papers)
- Cited by
- Industrial and Manufacturing EngineeringComputer Vision and Pattern RecognitionCivil and Structural Engineering
- Journals
- IEEE Transactions on Industrial ElectronicsExpert Systems with ApplicationsIEEE Transactions on Intelligent Transportation Systems
- Partner nations
- ChinaUnited Kingdom
In The Last Decade
Hongwen Dong
14 papers receiving 840 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Industrial and Manufacturing Engineering 505
- Computer Vision and Pattern Recognition 381
- Civil and Structural Engineering 292
- Mechanical Engineering 227
- Computational Mechanics 162
Countries citing papers authored by Hongwen Dong
This map shows the geographic impact of Hongwen Dong's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hongwen Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongwen Dong more than expected).
Fields of papers citing papers by Hongwen Dong
This network shows the impact of papers produced by Hongwen Dong. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hongwen Dong. The network helps show where Hongwen Dong may publish in the future.
Co-authorship network of co-authors of Hongwen Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Hongwen Dong. A scholar is included among the top collaborators of Hongwen Dong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hongwen Dong. Hongwen Dong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 8 | |
| 3 | 16 | |
| 4 | 34 | |
| 5 | 39 | |
| 6 | 29 | |
| 7 | 82 | |
| 8 | 17 | |
| 9 | 20 | |
| 10 | 64 | |
| 11 | 6 | |
| 12 | 22 | |
| 13 | 9 | |
| 14 | PGA-Net: Pyramid Feature Fusion and Global Context Attention Network for Automated Surface Defect Detectionbreakdown → | 379 |
| 15 | 129 |
About Hongwen Dong
Hongwen Dong is a scholar working on General Dentistry, Media Technology and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 854 indexed citations. Recurring topics across this work include Infrastructure Maintenance and Monitoring (6 papers), Advanced Image Fusion Techniques (4 papers) and Industrial Vision Systems and Defect Detection (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (505 citations), Computer Vision and Pattern Recognition (381 citations) and Civil and Structural Engineering (292 citations). Hongwen Dong has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Yunhui Yan, Kechen Song, Yu He, Jing Xu, Qinggang Meng, Yanyan Wang, Defu Zhang, Jie Liu, Shuai Ma and Hongkun Tian. Their work appears in journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and IEEE Transactions on Intelligent Transportation Systems.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.